Sanjay Padhi, Amazon Web Services
Data rich scientific instruments or domains like High Energy Physics (HEP) have driven innovation via data analytics using worldwide distributed storage and computing. With the evolution of cloud computing, common storage elements like Amazon S3, along with essential ingredients like elasticity, virtualization, serverless computing, etc. played prominent roles in modern day computing infrastructure. Today cloud services like AWS play a vital role in our daily lives. Currently, many modern instruments upload their data to cloud via edge devices and analytics on them is performed instantaneously either on streaming or resident data. Analytics on these Big Data from a myriad of sources gave rise to “smart” projects, such as Connected Intersections, Smart Cities, Smart Health, etc.
This talk will provide a range of examples from data collection to Machine Learning based analytics on the AWS platform. Supervised and unsupervised based learning frameworks using AWS and its implications in the fields of Agriculture, Medical Imaging, Cancer detection, etc. will be discussed. Next generation compute architectures (including FPGA based AWS F1 instances) and their roles in deep neural nets associated with image, text and natural language processing will be outlined. Amazon Artificial Intelligence (AI) framework including AI services, platform and engine will be discussed in the context of future online analysis platforms. Potential areas for collaboration with the AWS Research Initiative will also be presented.
Speaker Bio. Dr. Sanjay Padhi, leads the global AWS Research Initiatives as well as AWS’s federal initiative with the National Science Foundation. With a Ph.D. from McGill University in high energy physics, Dr. Padhi has more than 15 years of experience at CERN’s LHC in large-scale distributed computing, data analytics, and machine learning. He is also an adjunct associate professor of physics at Brown University.